Visualizing Geographical Information Through Tag Clouds

Davide Chiara (), Vincenzo Fatto () and Monica Sebillo ()
Additional contact information
Davide Chiara: University of Salerno
Vincenzo Fatto: University of Salerno
Monica Sebillo: University of Salerno

A chapter in Information Systems: Crossroads for Organization, Management, Accounting and Engineering, 2012, pp 209-216 from Springer

Abstract: Abstract In the last decade, the need to support decision makers in solving problems related to a territory and its phenomena has stimulated Geographic Information Visualization (GeoVis) researchers to propose highly interactive visualization tools able to both synthesize information from large datasets and perform complex analytical tasks. The goal of the present paper is to propose a GeoVis method based on a recent InfoVis technique, known as Tag Cloud, which combines tag clouds with advanced GeoVis techniques for visualizing geographic data and related spatio-temporal phenomena. The method elaborates a simplified map containing a georeferenced cloud of tags, placed where the associated information is appropriate and significant. As initial result a system prototype has been realized in order to obtain an overview of data distribution and classification. It is focused on data extraction and aggregation, and output visualization, and adopts various techniques to allow users to select data to visualize starting from a geographic dataset.

Keywords: Font Size; Cloud Generation; Free Form Text; Spatial Data Model; Label Placement (search for similar items in EconPapers)
Date: 2012
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-7908-2789-7_24

Ordering information: This item can be ordered from
http://www.springer.com/9783790827897

DOI: 10.1007/978-3-7908-2789-7_24

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().